Replace columns to NA for certain conditions in data frame

Question

Let's take the iris data frame.

Hypothetically, I know the guy that measured the Petal.Length, Petal.Width and Sepal.Width for the species setosa and know he made some terrible mistakes. Therefore I would like to make all these values NA. The Sepal.Length and all other data from the other species is measured by other people and can be trusted.

Is there an easy way to do this with dplyr or otherwise? For the real data frame there are many more columns that need to be changed to NA.

For example, `df[,c("a", "b")] <- NA` assigns `NA` to columns `a` and `b` of data frame `df`. — lukeA, Mar 08 '17 at 10:21
Are all columns in your df set to NA or do some keep their value? — Edwin, Mar 08 '17 at 10:23

score 0 · Accepted Answer · edited May 23 '17 at 12:17

0

Using iris data:

iris[ iris$Species == "setosa",
      c("Petal.Length", "Petal.Width", "Sepal.Width")] <- NA

dplyr solutions can be found at: dplyr mutate/replace on a subset of rows

edited May 23 '17 at 12:17

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answered Mar 08 '17 at 10:31

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Replace columns to NA for certain conditions in data frame

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